Design and development of an automated indoor position tagging system and autonomous navigation for a contact-based flying robot using sensor fusion and machine vision

Providing three-dimensional (3D) coordinates and more importantly drone navigation in GPS-denied environments has been always challenging. Limiting factors such as signal reflection from walls (multipath), lack of Global Positioning System (GPS) signals in confined spaces and non-line of sight (NLoS) communication with orbiting satellites, build a barrier to navigate indoor drones. In this work, we propose to add a navigation feature to Avestec’s tethered-drone along with extracting the 3D coordinates of the drone with centimeter accuracy while flying inside metallic enclosed spaces. These features include inspection data tagging and eliminating the entrance of human operators in confined environments by providing assistance to (semi-) autonomous navigation.

Faculty Supervisor:

Shahriar Mirabbasi;Michal Aibin

Student:

Partner:

Avestec Technologies Inc

Discipline:

Engineering

Sector:

Mining

University:

British Columbia Institute of Technology; The University of British Columbia

Program: